Comparison of baseline correction algorithms for in vivo 1H-MRS.

Proton MRS is used clinically to collect localized, quantitative metabolic data from living tissues. However, the presence of baselines in the spectra complicates accurate MRS data quantification. The occurrence of baselines is not specific to short-echo-time MRS data. In short-echo-time MRS, the baseline consists typically of a dominating macromolecular (MM) part, and can, depending on B0 shimming, poor voxel placement, and/or localization sequences, also contain broad water and lipid resonance components, indicated by broad components (BCs). In long-echo-time MRS, the MM part is usually much smaller, but BCs may still be present. The sum of MM and BCs is denoted by the baseline. Many algorithms have been proposed over the years to tackle these artefacts. A first approach is to identify the baseline itself in a preprocessing step, and a second approach is to model the baseline in the quantification of the MRS data themselves. This paper gives an overview of baseline handling algorithms and also proposes a new algorithm for baseline correction. A subset of suitable baseline removal algorithms were tested on in vivo MRSI data (semi-LASER at TE = 40 ms) and compared with the new algorithm. The baselines in all datasets were removed using the different methods and subsequently fitted using spectrIm-QMRS with a TDFDFit fitting model that contained only a metabolite basis set and lacked a baseline model. The same spectra were also fitted using a spectrIm-QMRS model that explicitly models the metabolites and the baseline of the spectrum. The quantification results of the latter quantification were regarded as ground truth. The fit quality number (FQN) was used to assess baseline removal effectiveness, and correlations between metabolite peak areas and ground truth models were also examined. The results show a competitive performance of our new proposed algorithm, underscoring its automatic approach and efficiency. Nevertheless, none of the tested baseline correction methods achieved FQNs as good as the ground truth model. All separately applied baseline correction methods introduce a bias in the observed metabolite peak areas. We conclude that all baseline correction methods tested, when applied as a separate preprocessing step, yield poorer FQNs and biased quantification results. While they may enhance visual display, they are not advisable for use before spectral fitting.

Subpixel motion artifacts correction and motion estimation for 3D-OCT.

A number of hardware-based and software-based strategies have been suggested to eliminate motion artifacts for improvement of 3D-optical coherence tomography (OCT) image quality. However, the hardware-based strategies have to employ additional hardware to record motion compensation information. Many software-based strategies have to need additional scanning for motion correction at the expense of longer acquisition time. To address this issue, we propose a motion artifacts correction and motion estimation method for OCT volumetric imaging of anterior segment, without requirements of additional hardware and redundant scanning. The motion correction effect with subpixel accuracy for in vivo 3D-OCT has been demonstrated in experiments. Moreover, the physiological information of imaging object, including respiratory curve and respiratory rate, has been experimentally extracted using the proposed method. The proposed method offers a powerful tool for scientific research and clinical diagnosis in ophthalmology and may be further extended for other biomedical volumetric imaging applications.

Assessing the distortions introduced when calculating d': A simulation approach.

The discriminability measure d ' is widely used in psychology to estimate sensitivity independently of response bias. The conventional approach to estimate d ' involves a transformation from the hit rate and the false-alarm rate. When performance is perfect, correction methods must be applied to calculate d ' , but these corrections distort the estimate. In three simulation studies, we show that distortion in d ' estimation can arise from other properties of the experimental design (number of trials, sample size, sample variance, task difficulty) that, when combined with application of the correction method, make d ' distortion in any specific experiment design complex and can mislead statistical inference in the worst cases (Type I and Type II errors). To address this problem, we propose that researchers simulate d ' estimation to explore the impact of design choices, given anticipated or observed data. An R Shiny application is introduced that estimates d ' distortion, providing researchers the means to identify distortion and take steps to minimize its impact.

Application of adaptive chaotic dung beetle optimization algorithm to near-infrared spectral model transfer.

A new transfer approach was proposed to share calibration models of the hexamethylenetetramine-acetic acid solution for studying hexamethylenetetramine concentration values across different near-infrared (NIR) spectrometers. This approach combines Savitzky-Golay first derivative (S_G_1) and orthogonal signal correction (OSC) preprocessing, along with feature variable optimization using an adaptive chaotic dung beetle optimization (ACDBO) algorithm. The ACDBO algorithm employs tent chaotic mapping and a nonlinear decreasing strategy, enhancing the balance between global and local search capabilities and increasing population diversity to address limitations observed in traditional dung beetle optimization (DBO). Validated using the CEC-2017 benchmark functions, the ACDBO algorithm demonstrated superior convergence speed, accuracy, and stability. In the context of a partial least squares (PLS) regression model for transferring hexamethylenetetramine-acetic acid solutions using NIR spectroscopy, the ACDBO algorithm excelled over alternative methods such as uninformative variable elimination, competitive adaptive reweighted sampling, cuckoo search, grey wolf optimizer, differential evolution, and DBO in efficiency, accuracy of feature variable selection, and enhancement of model predictive performance. The algorithm attained outstanding metrics, including a determination coefficient for the calibration set (Rc2) of 0.99999, a root mean square error for the calibration set (RMSEC) of 0.00195%, a determination coefficient for the validation set (Rv2) of 0.99643, a root mean squared error for the validation set (RMSEV) of 0.03818%, residual predictive deviation (RPD) of 16.72574. Compared to existing OSC, slope and bias correction (S/B), direct standardization (DS), and piecewise direct standardization (PDS) model transfer methods, the novel strategy enhances the accuracy and robustness of model predictions. It eliminates irrelevant background information about the hexamethylenetetramine concentration, thereby minimizing the spectral discrepancies across different instruments. As a result, this approach yields a determination coefficient for the prediction set (Rp2) of 0.96228, a root mean squared error for the prediction set (RMSEP) of 0.12462%, and a relative error rate (RER) of 17.62331, respectively. These figures closely follow those obtained using DS and PDS, which recorded Rp2, RMSEP, and RER values of 0.97505, 0.10135%, 21.67030, and 0.98311, 0.08339%, 26.33552, respectively. Unlike conventional methods such as OSC, S/B, DS, and PDS, this novel approach does not require the analysis of identical samples across different instruments. This characteristic significantly broadens its applicability for model transfer, which is particularly beneficial for transferring specific measurement samples.

AAV gene replacement therapy for treating MPS IIIC: Facilitating bystander effects via EV-mRNA cargo.

MPS IIIC is a lysosomal storage disease caused by mutations in heparan-α-glucosaminide N-acetyltransferase (HGSNAT), for which no treatment is available. Because HGSNAT is a trans-lysosomal-membrane protein, gene therapy for MPS IIIC needs to transduce as many cells as possible for maximal benefits. All cells continuously release extracellular vesicles (EVs) and communicate by exchanging biomolecules via EV trafficking. To address the unmet need, we developed a rAAV-hHGSNATEV vector with an EV-mRNA-packaging signal in the 3'UTR to facilitate bystander effects, and tested it in an in vitro MPS IIIC model. In human MPS IIIC cells, rAAV-hHGSNATEV enhanced HGSNAT mRNA and protein expression, EV-hHGSNAT-mRNA packaging, and cleared GAG storage. Importantly, incubation with EVs led to hHGSNAT protein expression and GAG contents clearance in recipient MPS IIIC cells. Further, rAAV-hHGSNATEV transduction led to the reduction of pathological EVs in MPS IIIC cells to normal levels, suggesting broader therapeutic benefits. These data demonstrate that incorporating the EV-mRNA-packaging signal into a rAAV-hHGSNAT vector enhances EV packaging of hHGSNAT-mRNA, which can be transported to non-transduced cells and translated into functional rHGSNAT protein, facilitating cross-correction of disease pathology. This study supports the therapeutic potential of rAAVEV for MPS IIIC, and broad diseases, without having to transduce every cell.

Using Flashcards and Descriptive Feedback to Teach Industrial Kitchen Equipment to a Student with Intellectual Disabilities in a Postsecondary Education Program.

With postsecondary education opportunities for adult students with intellectual and developmental disabilities (IDD) on the rise, it is important to find socially validated research-based methods that are appropriate for the university or other community-based postsecondary instructional settings. The present research examines the effects of using flashcards with descriptive feedback and opportunities to respond, to teach one student with intellectual disabilities, enrolled in a postsecondary education-training program, commonly used industrial kitchen equipment. Results showed that discrete trail instruction, which included an error correction strategy of descriptive feedback plus opportunities to correctly respond was highly effective in mastery and maintenance of kitchen equipment identification, and generalization when asked to locate those items in the university kitchen lab.

Predicting human effort needed to correct auto-segmentations.

Medical image auto-segmentation techniques are basic and critical for numerous image-based analysis applications that play an important role in developing advanced and personalized medicine. Compared with manual segmentations, auto-segmentations are expected to contribute to a more efficient clinical routine and workflow by requiring fewer human interventions or revisions to auto-segmentations. However, current auto-segmentation methods are usually developed with the help of some popular segmentation metrics that do not directly consider human correction behavior. Dice Coefficient (DC) focuses on the truly-segmented areas, while Hausdorff Distance (HD) only measures the maximal distance between the auto-segmentation boundary with the ground truth boundary. Boundary length-based metrics such as surface DC (surDC) and Added Path Length (APL) try to distinguish truly-predicted boundary pixels and wrong ones. It is uncertain if these metrics can reliably indicate the required manual mending effort for application in segmentation research. Therefore, in this paper, the potential use of the above four metrics, as well as a novel metric called Mendability Index (MI), to predict the human correction effort is studied with linear and support vector regression models. 265 3D computed tomography (CT) samples for 3 objects of interest from 3 institutions with corresponding auto-segmentations and ground truth segmentations are utilized to train and test the prediction models. The five-fold cross-validation experiments demonstrate that meaningful human effort prediction can be achieved using segmentation metrics with varying prediction errors for different objects. The improved variant of MI, called MIhd, generally shows the best prediction performance, suggesting its potential to indicate reliably the clinical value of auto-segmentations.

Osteotomies for genu varum: should we always correct at the tibia? A multicenter analysis of practices in France.

INTRODUCTION: Tibial correction is often performed during a valgus-producing osteotomy for genu varum. However, overcorrection and the creation of a joint line obliquity (JLO) have been associated with unfavorable functional outcomes after high tibial osteotomy (HTO). The aims of this study were to analyze 1) the corrections obtained after HTO, 2) the rationale behind the indication per the European Society for Sports Traumatology Surgery and Arthroscopy (ESSKA) recommendations, and 3) the correlation between the postoperative corrections obtained and functional outcomes. HYPOTHESIS: A significant number of patients who underwent an isolated HTO did not present an "ideal" theoretical indication based on the preoperative angles and correction targets to be performed. MATERIALS AND METHODS: This multicenter study included 289 isolated HTOs. Demographic and morphometric data were anonymized and compiled in a database. Preoperative radiographic parameters were compared with the ESSKA consensus recommendations on osteotomies for genu varum. The consensus defined the "ideal" indication for performing an HTO as medial tibiofemoral compartment pain with significant tibial varus deformity (medial proximal tibial angle [MPTA] < 85°), no significant femoral varus deformity (lateral distal femoral angle [LDFA] < 90°), an expected postoperative obliquity of less than 5°, and a correction resulting in moderate tibial valgus (postoperative MPTA < 94°). The incidence of patients with an "ideal" theoretical indication for isolated HTO and those with a theoretical indication not perfectly justified by the radiographic data and preoperative planning were recorded. RESULTS: Under the ESSKA consensus criteria, 25.3% (n = 73) of isolated HTOs, 15.6% (n = 45) of isolated femoral osteotomies, 9.3% (n = 27) of double-level osteotomies, and 49.9% (n = 144) of cases where no osteotomy was performed due to the lack of significant extra-articular tibial and/or femoral deformity were deemed justified. The presence of a preoperative femoral deformity and the absence of an "ideal" indication for HTO did not affect the postoperative Tegner Activity Scale or the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) scores (p > 0.05). A high preoperative hip-knee-ankle (HKA) angle and MPTA, which indicated less varus, were associated with a greater risk of there being no "ideal" theoretical indication for an HTO (coefficient of determination [R2] = 0.19 and R2 = 1, respectively; p < 0.001). CONCLUSION: This study showed that isolated HTOs in current practice were not justified in a significant number of patients, even though they could lead to tibial overcorrection and excessive JLO. This did not impact the functional results of this series, but it might complicate the performance of a secondary knee arthroplasty. Nevertheless, some young patients in this series underwent a salvage osteotomy outside the "ideal" indications of the European recommendations. LEVEL OF EVIDENCE: IV; case series.

Comparison of Surgical Burden, Radiographic and Clinical Outcomes According to the Severity of Baseline Sagittal Imbalance in Adult Spinal Deformity Patients.

OBJECTIVE: To determine the clinical impact of the baseline sagittal imbalance severity in patients with adult spinal deformity (ASD). METHODS: We retrospectively reviewed patients who underwent ≥ 5-level fusion including the pelvis, for ASD with a ≥ 2-year follow-up. Using the Scoliosis Research Society-Schwab classification system, patients were classified into 3 groups according to the severity of the preoperative sagittal imbalance: mild, moderate, and severe. Postoperative clinical and radiographic results were compared among the 3 groups. RESULTS: A total of 259 patients were finally included. There were 42, 62, and 155 patients in the mild, moderate, and severe groups, respectively. The perioperative surgical burden was greatest in the severe group. Postoperatively, this group also showed the largest pelvic incidence minus lumbar lordosis mismatch, suggesting a tendency towards undercorrection. No statistically significant differences were observed in proximal junctional kyphosis, proximal junctional failure, or rod fractures among the groups. Visual analogue scale for back pain and Scoliosis Research Society-22 scores were similar across groups. However, severe group's last follow-up Oswestry Disability Index (ODI) scores significantly lower than those of the severe group. CONCLUSION: Patients with severe sagittal imbalance were treated with more invasive surgical methods along with increased the perioperative surgical burden. All patients exhibited significant radiological and clinical improvements after surgery. However, regarding ODI, the severe group demonstrated slightly worse clinical outcomes than the other groups, probably due to relatively higher proportion of undercorrection. Therefore, more rigorous correction is necessary to achieve optimal sagittal alignment specifically in patients with severe baseline sagittal imbalance.

Required force for distraction during medial opening wedge high tibial osteotomy may serve as a predictive indicator for lateral hinge fracture.

Introduction: Medial open wedge high tibial osteotomy is a biological procedure for treating unicompartmental knee osteoarthritis. The literature repeatedly highlights the significance of preserving an intact lateral hinge during this procedure. We investigated the temporal course of distraction forces during distraction at the osteotomy site, aiming to quantitatively measure and analyse temporal changes in distraction forces at different distraction points for intact and fractured lateral hinges. Materials and Methods: This biomechanical study was conducted on 10 human cadavers, which were divided into two groups: one with preserved 1 cm intact lateral cortexes (ILCs) and the other with completely osteotomised fractured lateral cortexes (FLCs). An experimental setup was custom designed to facilitate the required force measurement during distraction. The distraction forces were recorded with a force gauge at 0.5-mm intervals throughout the distraction. Results: There was a significant difference between the ILC and FLC groups in distraction forces at all points (8-15 mm). The ILC group consistently exhibited higher distraction force values, with FLC recording values ranging from 8.8% to 13.2% of ILC's. Lateral hinge fractures caused an 86.7% reduction in the initial required force for distraction, significantly impacting the force required for distraction. The ILC group displayed a linear increase in the required distraction force up to 12.5 mm of distraction, which reached 3.7 times the initial value at 12.5 mm of distraction. The FLC group had lower baseline required distraction forces, following a relatively linear trend with more limited increases. Conclusion: FLCs in medial opening wedge osteotomy are associated with significant reductions in the force required for distraction, and a sudden decrease in distraction force during distraction may indicate a lateral hinge fracture. Force measurement devices for use during distraction could offer valuable insights and provide surgeons with immediate warnings for LHFs. Level of Evidence: Level IV.

Exploratory subgroup identification in the heterogeneous Cox model: A relatively simple procedure.

For survival analysis applications we propose a novel procedure for identifying subgroups with large treatment effects, with focus on subgroups where treatment is potentially detrimental. The approach, termed forest search, is relatively simple and flexible. All-possible subgroups are screened and selected based on hazard ratio thresholds indicative of harm with assessment according to the standard Cox model. By reversing the role of treatment one can seek to identify substantial benefit. We apply a splitting consistency criteria to identify a subgroup considered "maximally consistent with harm." The type-1 error and power for subgroup identification can be quickly approximated by numerical integration. To aid inference we describe a bootstrap bias-corrected Cox model estimator with variance estimated by a Jacknife approximation. We provide a detailed evaluation of operating characteristics in simulations and compare to virtual twins and generalized random forests where we find the proposal to have favorable performance. In particular, in our simulation setting, we find the proposed approach favorably controls the type-1 error for falsely identifying heterogeneity with higher power and classification accuracy for substantial heterogeneous effects. Two real data applications are provided for publicly available datasets from a clinical trial in oncology, and HIV.

Acesso a serviço de saúde e reabilitação auditiva de adultos e idosos durante o período inicial da pandemia COVID-19 no Brasil / Access to health service and hearing rehabilitation for adult and older adults during the initial period of the COVID-19 pandemic in Brazil / Acceso a servicios de salud yrehabilitación auditiva para adultos y ancianos durante el período inicial de la pandemia COVID-19 en Brasil

Introdução: A perda auditiva é uma deficiência comum na população mundial e contribui para dificuldade na comunicação verbal e redução da qualidade de vida, evidenciando a importância da identificação precoce, reabilitação e acompanhamento audiológico dessa deficiência para mitigar suas consequências. Durante a pandemia da COVID-19, as medidas restritivas diminuíram a capacidade de atendimento dos serviços de saúde auditiva e dificultaram a busca de auxílio para resolver problemas relacionados à adaptação aos dispositivos eletrônicos de amplificação sonora (DAES), sendo uma barreira no processo de reabilitação da perda auditiva. Objetivo: Caracterizar os usuários de DEAS e o processo inicial de reabilitação auditiva de adultos e idosos e verificar fatores associados ao retorno para a consulta de monitoramento auditivo durante o período inicial da pandemia da COVID-19.Métodos: Estudo observacional transversal com usuários adultos e idosos de um serviço ambulatorial de saúde auditiva com retorno para consulta de monitoramento auditivo agendada no período inicial da implementação das medidas restritivas da pandemia da COVID-19 no Brasil. Resultados: A maioria dos participantes conseguiu retornou para a consulta de monitoramento auditivo, sendo eles em sua maioria idosos, do sexo feminino e vacinados contra a COVID-19. Houve maior prevalência de adaptação adequada aos DAES. Não houve associação estatística entre as variáveis relacionadas à adaptação aos DAES, COVID-19 e saúde mental e o retorno à consulta de monitoramento auditivo. Conclusão: Os fatores relacionados à adaptação aos DAES, à COVID-19 ou à saúde mental não influenciaram o retorno à consulta de monitoramento auditivo na presente pesquisa. (AU)

Introduction: Hearing loss is a common disability in the world population and contributes to difficulty in verbal communication and reduced quality of life, highlighting the importance of early identification, rehabilitation and audiological monitoring of this disability to mitigate its consequences. During the COVID-19 pandemic, restrictive measures reduced the service capacity of hearing health services and made it difficult to seek help to solve problems related to adaptation to personal sound amplification products (PSAPs), being a barrier in the rehabilitation process of hearing loss. Aim: To characterize PSAPs users and the initial hearing rehabilitation process for adults and elderly people and verify the factors associated with the return to hearing monitoring consultations in the initial period of the COVID-19 pandemic. Methods: Cross-sectional observational study with adults and elderly people: elderly users of an outpatient hearing health service who return for a scheduled hearing monitoring consultation in the initial period of the implementation of restrictive measures of the COVID-19 pandemic in Brazil. Results: Most participants were able to return to the hearing monitoring clinic, the majority of whom were elderly, female and vaccinated against COVID-19. There was a higher prevalence of adequate adaptation to the PSAPs. There was no statistical association between variables related to adaptation to PSAPs, COVID-19 and mental health and return to hearing monitoring consultation. Conclusion: Factors related to adaptation to PSAPs, COVID-19 or mental health did not influence the return to hearing monitoring consultation in the present investigation. (AU)

Introducción: La pérdida auditiva es una discapacidad común en la población mundial y contribuye a la dificultad en la comunicación verbal y a la reducción de la calidad de vida, destacando la importancia de la identificación temprana, rehabilitación y seguimiento audiológico de esta discapacidad para mitigar sus consecuencias. Durante la pandemia de COVID-19, las medidas restrictivas redujeron la capacidad de atención de los servicios de salud auditiva y dificultaron la búsqueda de ayuda para resolver problemas relacionados con la adaptación a dispositivos electrónicos de amplificación del sonido (DEAS), siendo una barrera en el proceso de rehabilitación de la pérdida auditiva. Objetivo: Caracterizar a los usuarios de DEAS y el proceso inicial de rehabilitación auditiva de adultos y ancianos y verificar los factores asociados al retorno a las consultas de monitorización auditiva en el período inicial de la pandemia COVID-19. Métodos: Estudio observacional transversal con adultos y ancianos: ancianos usuarios de un servicio ambulatorio de salud auditiva que regresan para consulta de monitorización auditiva programada en el período inicial de la implementación de medidas restrictivas de la pandemia de COVID-19 en Brasil. Resultados: La mayoría de los participantes pudieron regresar a la clínica de monitorización auditiva, la mayoría de los cuales eran ancianos, mujeres y estaban vacunados contra COVID-19. Hubo mayor prevalencia de adaptación adecuada a la DEAS. No hubo asociación estadística entre variables relacionadas con adaptación a DEAS, COVID-19 y salud mental y retorno a consulta de monitorización auditiva. Conclusión: Los factores relacionados con la adaptación a DEAS, el COVID-19 o la salud mental no influyeron en el retorno a la consulta de monitorización auditiva en la presente investigación. (AU)

Coronary artery segmentation in CCTA images based on multi-scale feature learning.

BACKGROUND: Coronary artery segmentation is a prerequisite in computer-aided diagnosis of Coronary Artery Disease (CAD). However, segmentation of coronary arteries in Coronary Computed Tomography Angiography (CCTA) images faces several challenges. The current segmentation approaches are unable to effectively address these challenges and existing problems such as the need for manual interaction or low segmentation accuracy. OBJECTIVE: A Multi-scale Feature Learning and Rectification (MFLR) network is proposed to tackle the challenges and achieve automatic and accurate segmentation of coronary arteries. METHODS: The MFLR network introduces a multi-scale feature extraction module in the encoder to effectively capture contextual information under different receptive fields. In the decoder, a feature correction and fusion module is proposed, which employs high-level features containing multi-scale information to correct and guide low-level features, achieving fusion between the two-level features to further improve segmentation performance. RESULTS: The MFLR network achieved the best performance on the dice similarity coefficient, Jaccard index, Recall, F1-score, and 95% Hausdorff distance, for both in-house and public datasets. CONCLUSION: Experimental results demonstrate the superiority and good generalization ability of the MFLR approach. This study contributes to the accurate diagnosis and treatment of CAD, and it also informs other segmentation applications in medicine.

Identification and correction for collider bias in a genome-wide association study of diabetes-related heart failure.

Type 2 diabetes (T2D) is a major risk factor for heart failure (HF) and has elevated incidence among individuals with HF. Since genetics and HF can independently influence T2D, collider bias may occur when T2D (i.e., collider) is controlled for by design or analysis. Thus, we conducted a genome-wide association study (GWAS) of diabetes-related HF with correction for collider bias. We first performed a GWAS of HF to identify genetic instrumental variables (GIVs) for HF and to enable bidirectional Mendelian randomization (MR) analysis between T2D and HF. We identified 61 genomic loci, significantly associated with all-cause HF in 114,275 individuals with HF and over 1.5 million controls of European ancestry. Using a two-sample bidirectional MR approach with 59 and 82 GIVs for HF and T2D, respectively, we estimated that T2D increased HF risk (odds ratio [OR] 1.07, 95% confidence interval [CI] 1.04-1.10), while HF also increased T2D risk (OR 1.60, 95% CI 1.36-1.88). Then we performed a GWAS of diabetes-related HF corrected for collider bias due to the study design of index cases. After removing the spurious association of TCF7L2 locus due to collider bias, we identified two genome-wide significant loci close to PITX2 (chromosome 4) and CDKN2B-AS1 (chromosome 9) associated with diabetes-related HF in the Million Veteran Program and replicated the associations in the UK Biobank. Our MR findings provide strong evidence that HF increases T2D risk. As a result, collider bias leads to spurious genetic associations of diabetes-related HF, which can be effectively corrected to identify true positive loci.

Biosymbiotic haptic feedback - Sustained long term human machine interfaces.

Haptic technology permeates diverse fields and is receiving renewed attention for VR and AR applications. Advances in flexible electronics, facilitate the integration of haptic technologies into soft wearable systems, however, because of small footprint requirements face challenges of operational time requiring either large batteries, wired connections or frequent recharge, restricting the utility of haptic devices to short-duration tasks or low duty cycles, prohibiting continuously assisting applications. Currently many chronic applications are not investigated because of this technological gap. Here, we address wireless power and operation challenges with a biosymbiotic approach enabling continuous operation without user intervention, facilitated by wireless power transfer, eliminating the need for large batteries, and offering long-term haptic feedback without adhesive attachment to the body. These capabilities enable haptic feedback for robotic surgery training and posture correction over weeks of use with neural net computation. The demonstrations showcase that this device class expands use beyond conventional brick and strap or epidermally attached devices enabling new fields of use for imperceptible therapeutic and assistive haptic technologies supporting care and disease management.

High-Throughput Polar Code Decoders with Information Bottleneck Quantization.

In digital baseband processing, the forward error correction (FEC) unit belongs to the most demanding components in terms of computational complexity and power consumption. Hence, efficient implementation of FEC decoders is crucial for next-generation mobile broadband standards and an ongoing research topic. Quantization has a significant impact on the decoder area, power consumption and throughput. Thus, lower bit widths are preferred for efficient implementations but degrade the error correction capability. To address this issue, a non-uniform quantization based on the Information Bottleneck (IB) method is proposed that enables a low bit width while maintaining the essential information. Many investigations on the use of the IB method for Low-density parity-check code) LDPC decoders exist and have shown its advantages from an implementation perspective. However, for polar code decoder implementations, there exists only one publication that is not based on the state-of-the-art Fast Simplified Successive-Cancellation (Fast-SSC) decoding algorithm, and only synthesis implementation results without energy estimation are shown. In contrast, our paper presents several optimized Fast-SSC polar code decoder implementations using IB-based quantization with placement and routing results using advanced 12 nm FinFET technology. Gains of up to 16% in area and 13% in energy efficiency are achieved with IB-based quantization at a Frame Error Rate (FER) of 10-7 and a polar code of N=1024,R=0.5 compared to state-of-the-art decoders.

A Binocular Color Line-Scanning Stereo Vision System for Heavy Rail Surface Detection and Correction Method of Motion Distortion.

Thanks to the line-scanning camera, the measurement method based on line-scanning stereo vision has high optical accuracy, data transmission efficiency, and a wide field of vision. It is more suitable for continuous operation and high-speed transmission of industrial product detection sites. However, the one-dimensional imaging characteristics of the line-scanning camera cause motion distortion during image data acquisition, which directly affects the accuracy of detection. Effectively reducing the influence of motion distortion is the primary problem to ensure detection accuracy. To obtain the two-dimensional color image and three-dimensional contour data of the heavy rail surface at the same time, a binocular color line-scanning stereo vision system is designed to collect the heavy rail surface data combined with the bright field illumination of the symmetrical linear light source. Aiming at the image motion distortion caused by system installation error and collaborative acquisition frame rate mismatch, this paper uses the checkerboard target and two-step cubature Kalman filter algorithm to solve the nonlinear parameters in the motion distortion model, estimate the real motion, and correct the image information. The experiments show that the accuracy of the data contained in the image is improved by 57.3% after correction.

Erosion of Stumble Correction Evoked with Superficial Peroneal Nerve Stimulation in Older Adults during Walking.

In healthy young adults, electrical stimulation of the superficial peroneal cutaneous nerve (SPn) innervating the dorsum of the foot has been shown to elicit functionally relevant reflexes during walking that are similar to those evoked by mechanical perturbation to the dorsum of the foot during walking and are referred to as stumble corrective (obstacle avoidance) responses. Though age-related differences in reflexes induced by mechanical perturbation have been studied, toe clearance has not been measured. Further, age-related differences in reflexes evoked by electrical stimulation of SPn have yet to be determined. Thus, the purpose of this study was to characterize age-related differences between healthy young adults and older adults with no history of falls in stumble correction responses evoked by electrical stimulation of the SPn at the ankle during walking. Toe clearance relative to the walking surface along with joint displacement and angular velocity at the ankle and knee and EMG of the tibialis anterior, medial gastrocnemius, biceps femoris and vastus lateralis were measured. The combined background and reflex toe clearance was reduced in the older adults compared with the young in mid-early swing (p = 0.011). These age-related differences likely increase fall risk in the older adult cohort. Further, age-related changes were seen in joint kinematics and EMG in older adults compared with the young such as decreased amplitude of the plantarflexion reflex in early swing in older adults (p < 0.05). These altered reflexes reflect the degradation of the stumble corrective response in older adults.

Innovative approaches for accurate ozone prediction and health risk analysis in South Korea: The combined effectiveness of deep learning and AirQ.

Short-term exposure to ground-level ozone (O3) poses significant health risks, particularly respiratory and cardiovascular diseases, and mortality. This study addresses the pressing need for accurate O3 forecasting to mitigate these risks, focusing on South Korea. We introduce Deep Bias Correction (Deep-BC), a novel framework leveraging Convolutional Neural Networks (CNNs), to refine hourly O3 forecasts from the Community Multiscale Air Quality (CMAQ) model. Our approach involves training Deep-BC using data from 2016 to 2019, including CMAQ's 72-hour O3 forecasts, 31 meteorological variables from the Weather Research and Forecasting (WRF) model, and previous days' station measurements of 6 air pollutants. Deep-BC significantly outperforms CMAQ in 2021, reducing biases in O3 forecasts. Furthermore, we utilize Deep-BC's daily maximum 8-hour average O3 (MDA8 O3) forecasts as input for the AirQ+ model to assess O3's potential impact on mortality across seven major provinces of South Korea: Seoul, Busan, Daegu, Incheon, Daejeon, Ulsan, and Sejong. Short-term O3 exposure is associated with 0.40 % to 0.48 % of natural cause and respiratory deaths and 0.67 % to 0.81 % of cardiovascular deaths. Gender-specific analysis reveals higher mortality rates among men, particularly from respiratory causes. Our findings underscore the critical need for region-specific interventions to address air pollution's detrimental effects on public health in South Korea. By providing improved O3 predictions and quantifying its impact on mortality, this research offers valuable insights for formulating targeted strategies to mitigate air pollution's adverse effects. Moreover, we highlight the urgency of proactive measures in health policies, emphasizing the significance of accurate forecasting and effective interventions to safeguard public health from the deleterious effects of air pollution.